扩展企业管理模式下企业生产计划的特征

在企业的管理模式开始由以单个企业为核心向多个企业合作、共赢的扩展企业转变的环境下,分析了企业管理模式的变化,比较了基于扩展企业的管理模式与传统企业管理模式下生产计划的差异和特征,探讨了基于扩展企业管理模式企业生产计划的特点及制定生产计划面临的主要问题。     

因特网环境下的企业生产计划与控制

因特网的出现和发展,给现代企业带来了严重的挑战和巨大的机遇。本文研究因特网的应用对企业传统生产计划与控制方法的以及适合因特网环境的生产计划一控制的新模式和新方法。     

基于知识的生产计划与控制

错综复杂的产品结构和制造结构迫使企业对其后勤保障结构进行经常性的优化，并因此实现面向目标的生产计划与控制。在这一点上，知识资源愈来愈显示出其重要意义。特别是在信息与知识的相互交错中，传统的信息系统显示出其明显的缺陷。例如，这些缺陷可以通过基于知识的生产计划与控制得以平衡。     

生产计划制定过程的分析及数学建模

通过对某企业中MTO和ATO混合生产方式的分析，建立了描述其生产计划制定过程的数学模型。生产计划与调度是整个生产管理过程的核心，也是ERP系统中的核心模块。该项研究为企业生产管理规范了流程，为实施ERP系统提供了理论和逻辑基础。     

提高生产计划管理的几点建议

随着经济和科学技术的进步,如何做好企业产品的生产,保障产品的顺利交付是企业生产计划管理的重要内容,企业的正常计划包括对于生产过程中的人员安排、设备的配置、生产物料的供给、产品生产的工艺与工序的编排以及对于产品的品质的控制等方面。如何做好以上这些计划并做好企业的生产计划管理工作是十分重要的内容。本文主要对生产计划管理的内容进行介绍。     

推拉结合的生产计划与控制方法的应用研究

为解决制造企业生产系统面临的多品种、小批量的计划与控制问题，参考当前流行的生产管理理论，提出了一种推拉结合的生产计划与控制方法．该方法将MRP、JIT和TOC理论在不同计划和控制层面上进行综合应用，辅助车间快速有效地实现生产作业控制．该方法在制造执行系统（MES）平台的具体实现及在某制造型企业的应用验证了其可行性和有效性．     

面向订货生产的生产计划与控制技术

生产负荷控制是一种面向订货生产方式的生产计划与控制技术．它以输入输出控制为基本思想,通过设置订单交货期和控制订单进入生产车间的时间以及调整机器生产能力来控制各台机器的生产负荷,能够降低在制品库存,控制生产提前期并改善交货表现,从而增强制造企业的竞争力．本文介绍了生产负荷控制技术的理论、控制结构,并综述了相关研究文献,提出了今后的研究方向．     

面SCM生产计划与控制系统总体模型

研究供应链管理环境下企业生产计划与控制方法,分析了供应链环境下生产计划与控制系统的几个概念扩展,提出了生产组织新模式,探讨了新生产模式的计划信息组织与决策过程的几个特征,提出生产计划与控制总体模型,分析了模型的特点。     

单元化制造的生产计划和控制模式研究

针对某类产品单元化制造中单一的MRPⅡ、JIT或TOC生产计划和控制模式难以实施的特点,构建了一种以TOC、MRPⅡ生产计划系统和JIT生产控制系统为核心,考虑制造单元资源约束和订单插入因素的集成生产计划和控制模式.该模式能以市场需求预测、JIT拉动与APS模拟相结合的方式进行生产计划排产,同时利用能力需求计划、看板系统和系统仿真对生产过程实施跟踪控制.此模式对快速、有效地组织该类产品的生产具有重要意义.     

某石油化工公司生产计划优化研究

在某石化公司现行方法的基础上，根据石化企业的基本特点，将投入产出分析同线性规范有机地结合起来，为该公司生产计划的编制提供了一种新的方法。该方法在满足生产工艺流程要求的前提下，将产品市场需求，产品库存控制和生产计划的编制紧密结合起来，提高了生产计划工作的效率，保证了生产计划的实用性和适应性，提高了企业的经济效益。     

基于OPT的生产作业计划与控制系统设计

建立符合我国企业实际情况的生产作业计划与控制系统是我国企业现代化改造和适应新的生产方式的主要问题之一。论述了建立生产作业计划与控制系统模型的基本方法,以最优化生产技术（ＯＰＴ）的基本原理为基础,结合我国企业的实际情况,对现代制造系统生产作业计划与控制系统的编制方法进行了探讨和开发应用。     

Two-stage stochastic master production scheduling under demand uncertainty in a rolling planning environment

This paper proposes a scenario-based two-stage stochastic programming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and control system that is common in industrial practice. To reduce the problem of the disaggregation of the master production schedule, we use a relatively low aggregation level (compared to other work on stochastic programming for production planning). Consequently, we must consider many more scenarios to model demand uncertainty. Additionally, we modify standard modelling approaches for stochastic programming because they lead to the occurrence of many infeasible problems due to rolling planning horizons and interdependencies between master production scheduling and successive planning levels. To evaluate the performance of the proposed models, we generate a customer order arrival process, execute production planning in a rolling horizon environment and simulate the realisation of the planning results. In our experiments, the tardiness of customer orders can be nearly eliminated by the use of the proposed stochastic programming model at the cost of increasing inventory levels and using additional capacity.     

多重入晶圆制造厂整合式生产控制系统建模

将生产计划与生产调度整合,提出整合式晶圆生产控制系统,以应对生产过程中的异常情况,提高晶圆厂的生产绩效.利用两大建模工具IDEF0和Petri Net的各自优点,对整合式生产控制系统建模.     

A capacity-oriented hierarchical approach to single-item and small-batch production planning using project-scheduling methods

Most production planning and control (PPC) systems used in practice have an essential weakness in that they do not support hierarchical planning with feedback and do not observe resource constraints at all production levels. Also, PPC systems often do not deal with particular types of production, for example, low-volume production. We propose a capacity-oriented hierarchical approach to single-item and small-batch-production planning for make-to-order production. In particular, the planning stages of capacitated master production scheduling, multi-level lot sizing, temporal and capacity planning, and shop floor scheduling are discussed, where the degree of aggregation of products and resources decreases from stage to stage. It turns out that the optimization problems arising at most stages can be modelled as resourceconstrained project scheduling problems.     

虚拟企业生产计划与控制问题研究

着重分析了虚拟企业的特征及其生产系统构成模式，虚拟企业生产计划与控制的特点及其重点和难点，在此基础上，提出了虚拟企业生产计划与控制的策略，以为虚拟企业这种新型组织形式的生产管理提供参考。     

Design of predictable production scheduling model using control theoretic approach

As one of the most important planning and operational issues in manufacturing systems, production scheduling generally deals with allocating a set of resources over time to perform a set of tasks. Recently, control theoretic approaches based on nonlinear dynamics of continuous variables have been proposed to solve production scheduling problems as an alternative to traditional production scheduling methods that deal with decision-making components in discrete nature. The major goal of this paper is to improve predictability and performance of an existing scheduling model that employs the control theoretic approach, called distributed arrival time controller (DATC), to manage arrival times of parts using an integral controller. In this paper, we first review and investigate unique dynamic characteristics of the DATC in regards to convergence and chattering of arrival times. We then propose a new arrival time controller for the DATC that can improve predictability and performance in production scheduling. We call the new mechanism the double integral arrival-time controller (DIAC). We analyse unique characteristics of the DIAC such as oscillatory trajectory of arrival times, their oscillation frequency, and sequence visiting mechanism. In addition, we compare scheduling performance of the DIAC to the existing DATC model through computational experiments. The results show that the proposed system can be used as a mathematical and simulation model for designing adaptable manufacturing systems in the future.     

The industrial management of SMEs in the era of Industry 4.0

Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.     

Mixed-Integer Linear Programming approaches to shelf-life-integrated planning and scheduling in yoghurt production

In the production of perishable products such as dairy, meat or bakery goods, the consideration of shelf life in production planning is of particular importance. Retail customers with relatively low inventory turns can benefit significantly from longer product shelf life as wastage and out-of-stock rates decrease. However, in today's production planning and control systems, shelf-life issues with regard to specific products or customers are only seldom accounted for. Therefore, the objective of this paper is to develop Mixed-Integer Linear Programming (MILP) models that integrate shelf-life issues into production planning and scheduling. The research is based on an industrial case study of yoghurt production. Relying on the principle of block planning, three different MILP models for weekly production planning are presented that apply a combination of a discrete and continuous representation of time. Overnight production and, hence, the necessity for identifying two different shelf-life values for the same production lot is included in the model formulation. Numerical experiments show that near-optimal solutions can be obtained within reasonable computational time.     

Aggregate production planning in the automotive industry with special consideration of workforce flexibility

We present a new mixed integer linear programming approach for the problem of aggregate production planning of flowshop production lines in the automotive industry. Our model integrates production capacity planning and workforce flexibility planning. In contrast to traditional approaches, it considers discrete capacity adaptations which originate from technical characteristics of assembly lines as well as from work regulations and shift planning. In particular, our approach takes change costs into account and explicitly represents a working time account via a linear approximation. A solution framework containing different primal heuristics and preprocessing techniques is embedded into a decision support system. Finally, we present an illustrative case study and computational results on problem instances of practically relevant complexity.